论文标题
稀疏的时变参数vecms具有对电价建模的应用
Sparse time-varying parameter VECMs with an application to modeling electricity prices
论文作者
论文摘要
在本文中，我们提出了一个随时间变化的参数（TVP）矢量误差校正模型（VECM），并具有异性疾病。我们建议以自动方式执行动态模型规范的工具。这涉及使用全局本地先验，并在参数后处理以实现真正的稀疏解决方案。根据各自的系数集，我们通过最大程度地减少辅助损失函数来实现这一目标。我们的两步方法限制过度拟合并减少了参数估计不确定性。我们将此框架应用于建模欧洲电价。当共同考虑不同市场的每日电价时，我们的模型强调了明确解决协整和非线性的重要性。在一项针对德国小时价格的预测演习中，我们的方法产生了预测准确性的竞争指标。
In this paper we propose a time-varying parameter (TVP) vector error correction model (VECM) with heteroskedastic disturbances. We propose tools to carry out dynamic model specification in an automatic fashion. This involves using global-local priors, and postprocessing the parameters to achieve truly sparse solutions. Depending on the respective set of coefficients, we achieve this via minimizing auxiliary loss functions. Our two-step approach limits overfitting and reduces parameter estimation uncertainty. We apply this framework to modeling European electricity prices. When considering daily electricity prices for different markets jointly, our model highlights the importance of explicitly addressing cointegration and nonlinearities. In a forecast exercise focusing on hourly prices for Germany, our approach yields competitive metrics of predictive accuracy.
